本文针对无人机LiDAR点云地物分类问题，提出了一种基于改进的卷积神经网络模型，通过对四川某地区采集的点云数据进行人工标注，实现了地面、建筑和植被三种地物的点云分类。利用所设计的CNN模型对人工构建的数据集进行模型训练及测试，并不断对模型参数进行优化，总体分类精度 (OA)可达93.6599%。实验结果表明，本文所设计的改进CNN能够自动学习点云的空间分布特征和形状模式，减少了人工特征设计的工作量 ...

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